code: def testConstraintViolationMetric(
      self, batch_size, threshold, expected_result
  ):
      traj = self._create_test_trajectory(batch_size)
      num_actions = batch_size / 2
  
      obs_spec = tensor_spec.TensorSpec([], tf.float32)
      time_step_spec = ts.time_step_spec(obs_spec)
      action_spec = tensor_spec.BoundedTensorSpec(
          dtype=tf.int32, shape=(), minimum=0, maximum=num_actions - 1
      )
      stc = SimpleThresholdConstraint(
          time_step_spec,
          action_spec,
          batch_size=batch_size,
          threshold=threshold,
      )
      metric = tf_metrics.ConstraintViolationsMetric(constraint=stc)
      self.evaluate(metric.init_variables())
      traj_out = metric(traj)
      deps = tf.nest.flatten(traj_out)
      with tf.control_dependencies(deps):
          result = metric.result()
      result_ = self.evaluate(result)
      self.assertEqual(result_, expected_result)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import tensorflow
  from tf_agents.bandits.metrics import tf_metrics
  from tf_agents.bandits.policies import constraints
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import time_step
  from tf_agents.trajectories import trajectory
label_desc: Use image node_id 9 for calling the TFMetricsTest obj's underlying member method code with example usage: obj.testConstraintViolationMetric(batch_size, threshold, expected_result) without return types